Nitrogen Fertilization on a Soybean Crop Grown on Black Oat and Forage Pea Straw in a Clayey Latosol in Western Paraná
Bibliographic record
Abstract
The beneficial effects to the soil, when using cover crops, are numerous, such as nutrient cycling, nitrogen fixation, breaking of the cycle of pests and diseases, soil structuring and addition of dry matter. This makes the subsequent crop better able to express its productive potential. The nitrogen is a key element for any plant, especially in the early stages of crop development. In this way, the purpose of this study work was to evaluate the effect of nitrogen doses on the grain yield of soybeans grown on black oat and forage pea straw in a clayey Latosol in the western region of Paraná, Brazil. The experiment was conducted in the experimental area of the Agronomic Institute of Paraná (IAPAR), in the regional hub of Santa Tereza do Oeste. The local soil is classified as a typical Dystrophic Red Latosol. The experimental design consisted of a randomized complete block design with five replicates. The treatments consisted of nitrogen doses of 0, 25, 50, 75 and 100 kg ha-1 applied in a broadcasting cover, without incorporation, using urea as a nitrogen source, at 20 days after emergence when the plants were in stage V3. The soil physical attributes were bulk density, total porosity, microporosity, and macroporosity. In the soybean crop, the production components evaluated were: plant height, 100-grain weight, and grain yield of grains. The data were submitted to analysis of variance, in which, for the quantitative factors, a regression analysis was performed and, for the qualitative characteristics, the Tukey test (p < 0.05) was performed. The mineral addition of nitrogen did not lead to an increase in grain yield of the cultivated soybean on the species of oat or forage pea cover. Thus, it can be stated that in well-structured clayey Latosols with high fertility, the nitrogen present in the soil organic matter and what was fixed symbiotically is sufficient to supply the nitrogen demand for the soybean crop.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".